What is Customer Lifetime Value (CLV)?
Customer lifetime value, also known as CLV or CLTV, calculates a hard value for the financial relationship between a business and a customer by measuring the entire revenue that a customer will likely spend on a business or product over a designated period of time.
If a customer is a loyalist to a specific airline’s frequent flier perks, for example, their customer lifetime value will likely be far greater than a similar traveler who airline-hops in search of the best flight schedules or the lowest fares.
What Does “Lifetime” Mean?
Despite its name, CLV does not measure the entire lifetime of a customer. Instead it refers to the lifetime of the relationship between the customer and the business. A new parent might have a brand lifetime of five to ten years in which they purchase baby clothes or formula, while a frequent business traveler may have a much longer lifetime with an airline, hotel brand, or business travel credit card.
Why is a CLV analysis important?
Understanding a customer’s CLV – or their long-term value – helps businesses define how much they should invest in acquiring new customers and how much they should spend to retain current ones. What’s more, the CLV can also help businesses determine how much to invest to potentially elevate a customer into a premiere or preferred buyer status.
Knowing that a consumer spends $150 a month on their drive-through coffee purchases can help a brand determine how much to spend to maintain that relationship. Beyond loyalty to a specific brand, the CLV can also measure engagement across a category–does your customer also buy coffee at other retailers–and assess how their coffee-purchase behavior changes over time.
How do you analyze and calculate CLV?
Analyzing CLV starts with identifying users who are new to a brand and then examining how much they spend during a given time period. A deeper analysis will then segment customers into tiers based on their ongoing engagement with the brand and category.
Key metrics used in a CLV analysis include:
- Retention: Tracks what portion of new shoppers to a brand continue to buy the brand in subsequent years and also tracks if shoppers continue to buy the same category in subsequent years. In other words, if a person buys lipstick this year, will they continue to do so in future years? Do they also buy other makeup products and will they continue to do so?
- Buy Rate: This is the heart of the CTLV analysis. How much long-term revenue should I expect from a new shopper to my brand? Do I expect this user to buy one lipstick a year or six per year, and for how many years will they buy lipstick at this rate?
- Category Engagement (Loyalty): Helps clients understand how shoppers are engaging with the rest of the category by detailing the share of requirements and the average number of parent brands being purchased by their shoppers. Are customers only buying lipstick from one brand? Or are they buying other makeup products? Are those other products being purchased from one brand or across multiple brands?
Challenges with calculating CLV
While calculating the lifetime value of your customers as an incredibly useful metric, it can also be time consuming to calculate. Calculating this value relies on comprehensive datasets that aren’t always readily available. What’s more, segmenting and studying customers over an extended period of time is a very time-intensive process, which means it can be prohibitive to create this type of study at scale.
Additionally, most traditional panels are unable to track individual households (HH’s) across multiple buying channels – which means the data from most CLTV tracking is inaccurate. Traditional panels also usually lack the long-term relationship with panelists that would be required to analyze any “lifetime” buying patterns.
At Numerator, the sheer size of our panel provides us with a larger sample to analyze. Importantly, we also have a strict requirement that panelists must have been a part of the panel for a minimum number of years, which is a necessity to conduct this type of analysis.
What determines a “good” CLV?
Consistent data is key when it comes to analyzing a “good” CLV. Querying consumers only once or twice will lead to gaps in information which will produce an inaccurate CLTV.
A data insights company must be able to segment customers based on how they engage with a product over time. This is important because customers can be inconsistent in their purchase patterns in any given time period–for example, they may buy six lipsticks one year but only three in the next two years. A “good” CLV will help brands understand how a customer’s value changes and if the brand has been successful at retaining this shopper.
What you can learn from a CLV analysis
Not only does a CLV analysis tell you how valuable a customer is to your brand or product, but it will help businesses justify how much they should budget for their sales and marketing efforts. Additionally, good CLV data will help brands understand the average retention of buyers over a period of time and how that retention has changed.
By identifying the gaps–where buyers buy the category but not the brand–businesses can adjust their outreach to adjust the retention of their customers.
How to increase CLV
Increasing product consumption is the shortest path to an increased CLTV, so paying attention to and increasing the hard metrics is key. These metrics include:
- Increased purchase frequency
- Increased spend per trip
- Increased units per trip
- Increased spend per unit
- Increased retention (getting buyers to engage with your product longer)
But driving increased spending isn’t as easy as flipping a switch. Brands must provide value to their consumers, so driving change requires that products:
- Solve a consumer problem better than its competitors
- Provide more value to consumers than its competitors
- Have more impactful marketing and promotional strategies that will help acquire and keep customers
What are the main drivers of CLV?
As outlined above, retention, buy rate and loyalty are the main drivers of CLV. As such, brands (and their data insights partners) should be asking the following questions:
Get your own CLV analysis with Numerator.
For more information contact your Numerator representative or reach out to us to learn how you can calculate and optimize the Customer Lifetime Value for your brand.